The Team:

The Analytics team at Upstart is at the forefront of AI/ML-driven credit lending across the organization. Our team employs advanced analytical and technical prowess to deliver comprehensive support in Upstart’s lending platform. The Credit Analytics team is building out foundational frameworks and infrastructures on loan performance and forecasting, market cycles and emerging trends, risk and return trade-offs, among others. We also take pride in developing our business intelligence tools to empower self-service reporting and streamlining work processes through automation.

As a Senior Analyst at Upstart, you will join our Credit Analytics horizontal team. You’ll take a leadership stance in driving critical insights and decisions concerning credit performance and strategies, and contributing to the long term development in underwriting framework and analytics infrastructure. Collaborating closely with other Data Analytics, Machine Learning, and Product teams, you will spearhead initiatives that support Upstart’s multi-product growth and extend our market leadership in lending.

How you’ll make an impact:

• Partner with the Data Analytics vertical teams, Machine Learning, Product, Engineering, and Finance teams to shape credit metrics and narratives, financial forecast, and driving consensus in the state of Upstart platform
• Influence Upstart’s credit platform and investor/lending community through informing decisions, opportunities, and risks, while supported by deep understanding and insights on Upstart’s machine learning model, credit, and valuation
• Lead and develop analytics on underwriting decisions, credit monitoring, model impacts, asset forecast, and valuation modeling to conduct in-depth analyses on credit data, trends, and anomalies that drive model and product decisions
• Build foundational forecast models, data pipelines, and automated reporting to enable robust and dynamic credit intelligence for Upstart analyst community
• Mentor junior team members on best practices and foster a center of excellence on data, credit, and analytics

What we’re looking for: 

• Minimum qualifications:
  • 5+ years in professional experience with demonstrated growth in technology and financial industry
  • Experience in credit analytics, valuation, and/or quantitative financial model development with Python, R, & SQL 
  • Experience in decisioning supported by large datasets, data modeling, and data pipelines using tools like Databricks, DBT, Looker, Snowflake, & Redshift
  • Degree in Economics, Statistics, Engineering, Data Science or other quantitative fields
• Preferred qualifications:
  • Demonstrated ability to work collaboratively and in deep partnership with cross-functional colleagues especially in Finance, Product, Data Engineering, ML teams
  • Ability to craft executive-ready narratives around complex business or performance topics, leveraging visualization and dashboards (e.g., Tableau, PowerBI, Looker), and to successfully influence and drive C-level decision-making
  • Experience in consumer lending strategy, and/or investment experience in consumer credit capital markets, private credit, structured products
  • Experience in coaching and mentoring junior team members on technical subjects

Position location - This role is available in the following locations: Remote

Time zone requirements - The team operates on the West coast time zones.

Travel requirements - As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

What you'll love: 

• Competitive Compensation (base + bonus & equity)
• Comprehensive medical, dental, and vision coverage
• Personal Development and Technology & Ergonomic Budgets 
• Life insurance and disability benefits 
• Clubs and Activities  (Game Nights, Fitstarters, Superwomen, Book Club, Investing Club, Money Discussions, Photography Club and Basketball teams) 
• Generous vacation policy
• 401(k) and Employee Stock Purchase Plan (ESPP)
• Catered lunches + snacks & drinks

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